Fibre orientation atlas guided rapid segmentation of white matter tracts

Abstract Fibre tract delineation from diffusion magnetic resonance imaging (MRI) is a valuable clinical tool for neurosurgical planning and navigation, as well as in research neuroimaging pipelines. Several popular methods are used for this task, each with different strengths and weaknesses making them more or less suited to different contexts. For neurosurgical imaging, priorities include ease of use, computational efficiency, robustness to pathology and ability to generalise to new tracts of interest. Many existing methods use streamline tractography, which may require expert neuroimaging operators for setting parameters and delineating anatomical regions of interest, or suffer from as a lack of generalisability to clinical scans involving deforming tumours and other pathologies. More recently, data‐driven approaches including deep‐learning segmentation models and streamline clustering methods have improved reproducibility and automation, although they can require large amounts of training data and/or computationally intensive image processing at the point of application. We describe an atlas‐based direct tract mapping technique called ‘tractfinder’, utilising tract‐specific location and orientation priors. Our aim was to develop a clinically practical method avoiding streamline tractography at the point of application while utilising prior anatomical knowledge derived from only 10–20 training samples. Requiring few training samples allows emphasis to be placed on producing high quality, neuro‐anatomically accurate training data, and enables rapid adaptation to new tracts of interest. Avoiding streamline tractography at the point of application reduces computational time, false positives and vulnerabilities to pathology such as tumour deformations or oedema. Carefully filtered training streamlines and track orientation distribution mapping are used to construct tract specific orientation and spatial probability atlases in standard space. Atlases are then transformed to target subject space using affine registration and compared with the subject's voxel‐wise fibre orientation distribution data using a mathematical measure of distribution overlap, resulting in a map of the tract's likely spatial distribution. This work includes extensive performance evaluation and comparison with benchmark techniques, including streamline tractography and the deep‐learning method TractSeg, in two publicly available healthy diffusion MRI datasets (from TractoInferno and the Human Connectome Project) in addition to a clinical dataset comprising paediatric and adult brain tumour scans. Tract segmentation results display high agreement with established techniques while requiring less than 3 min on average when applied to a new subject. Results also display higher robustness than compared methods when faced with clinical scans featuring brain tumours and resections. As well as describing and evaluating a novel proposed tract delineation technique, this work continues the discussion on the challenges surrounding the white matter segmentation task, including issues of anatomical definitions and the use of quantitative segmentation comparison metrics.

metrics, neither method stands out as being more accurate when trained and tested against the same data.(Wasserthal, Neher, and Maier-Hein, 2018b) This figure can be directly compared with Figure 6. in Wasserthal, Neher, and Maier-Hein (2018b), see Wasserthal, Neher, and Maier-Hein (2018a) for full tract names.

Corticospinal tract
Standardised white matter atlases and tractography protocols varyingly describe the corticospinal and pyramidal tracts.These two terms are often used interchangeably in tractography-oriented publications, while in anatomical terms they are distinct: The corticospinal (CST) and pyramidal tracts (PyT) are both descending motor pathways, with the PyT encompassing both the CST and the corticobulbar tract, which controls movement of the head, neck and face via the cranial nerves.Tractography studies and related white matter segmentation research frequently conflate the major descending (motor) and ascending (sensory pathways).This is evident in two main regions.Firstly, the inclusion of the medial lemniscus is frequently seen in PyT or CST segmentations (usually as it is not explicitly excluded, rather than being actively included).This includes TractSeg (and associated reference streamline bundles), XTRACT to some extent, and TractoInferno.By contrast, the tractography protocol employed in this research includes an exclusion mask on the medial lemniscus.
Secondly, while it has been suggested that the primary motor cortex can reside in the post-central gyrus, (Kumar et al., 2009) it is generally accepted that the somatosensory cortex is located in the latter, while the motor areas are in the precentral gyri.However, particularly with probabilistic tractography, it is near impossible to constrain streamlines exiting the internal capsule into the fanning corona radiata to one side of the central sulcus, without additional exclusion planes or the use of cortical target regions, which are especially time-consuming to produce, whether manually or through automatic parcellation.Thus streamline-based CST segmentations often contain parts of the somatosensory cortex while others, such as those utilising cortical parcellation-derived target regions, will be restricted to the motor cortex.
The tractfinder CST atlas streamlines were obtained using Freesurfer parcellations (Desikan et al., 2006;Fischl et al., 2002) of the primary motor cortex, as are the TractSeg reference bundles.TractInferno reference bundles for the pyramidal tracts include sensory cortex.

Optic radiation
When it comes to the course of the optic radiations through the sagittal stratum and posterior termination in the occipital lobes, there is no disagreement between segmentation approaches.However, there remain significant differences in the regions of the lateral geniculate nucleus (LGN) and Meyer's loop.The LGN is a small nucleus of the thalamus from which the neurons of the OR originate.Its localisation on MRI images is not straightforward, and due to the complex arrangement of white matter structures in the upper midbrain and thalamus regions, it is easy for streamlines to extend into the entire posterior thalamus and fornix and even descend into the brainstem.This contributes to often broad OR segmentations in the thalamic portion at the start of the tract.Secondly, the full anterior extent of Meyer's loop is often not reconstructed by tractography, due to the extreme and tight curvature.(Lilja and Nilsson, 2015;Chamberland, Tax, and Jones, 2018) Arcuate fasciculus and inferior fronto-occipital fasciculus Of the tracts studied in this work, the arcuate fasciculus (AF) and inferior fronto-occipital fasciculus (IFOF) exhibit the most extreme variability in segmented anatomical extent.This is partially owing to disagreements in definition, as they are both association pathways, making agreements about their function and precise cortical targets hard to find.For example, while the general consensus is that the AF connects the temporal and frontal language areas, XTRACT follows the "three part" paradigm (Catani, Jones, and Ffytche, 2005) which includes a third cortical termination region in the supramarginal gyrus, or inferior parietal cortex.
There are also controversies about whether the IFOF terminates in the parietal and temporal, in addition to the occipital lobes, (Martino et al., 2010;Forkel et al., 2014;Weiller et al., 2021) with some suggesting it be subdivided into two components based on these posterior terminations.(Martino et al., 2010;Sarubbo et al., 2013;Rollans and Cummine, 2018) Furthermore, unless cortical parcellation derived termination masks are utilised, it is practically impossible to constrain streamlines to a compact pathway, with bundles frequently terminating within large swathes of the frontal and temporal lobes.

D Tractography ROIs and parameters D.1 ROI definitions
The following ROI strategies were used for atlas constructions and subsequent validation tractography (differences between the two specified where applicable).Visualisations of each ROI are shown on MNI152 template in Figures D.3,D.4 and D.6.
locating the central sulcus (Fig. D.3, arrow).Include Descending section of the arcuate fasciculus, drawn on the axial plane Exclude Exclusion ROIs targeting: midline, superior fronto-occipital fasciculus, ipsilateral cerebral penduncles, sagittal stratum, corona radiata and external capsules.The following publications were reviewed to inform the above ROI strategy: Brown et al. (2014), Catani et al. (2002), Catani, Jones, and Ffytche (2005), Chen et al. (2015), Eluvathingal et al. (2007), Kamali et al. (2014), Martino et al. (2013), Nucifora et al. (2005), Parker et al. (2005), Bain et al. (2019), and Talozzi et al. (2018)Corticospinal tractCorticospinal tract tracography strategy differed between the atlas creation and general tractography applied to new subjects.Seed (atlas) For the orientation atlas, Freesurfer cortical parcellations were used to obtain more complete coverage of the motor cortex via the following process:1.Seed in precentral gyrus and output successful seed location 2. Generate binary mask from successful seed locations, subtract from precentral gyrus mask to create seed mask 3. Re-run tractography with second seed mask to cover rest of precentral gyrus Seed (general) Posterior limb of internal capsule, drawn on 3 consecutive axial slices Include Posterior limb on internal capsule (if not used for seed), cerebral penduncles, CST in mid-pons

Figure D. 3
Figure D.3 Seed (yellow), inclusion (green) and exclusion (red) regions of interest for the arcuate fasciculus.Arrow indicates central sulcus, landmark for seed ROI.

Figure D. 4
Figure D.4 Seed (yellow), inclusion (green) and exclusion (red) regions of interest for the corticospinal tract

Figure D. 5
Figure D.5 Seed (yellow), inclusion (green) and exclusion (red) regions of interest for the inferior fronto-occipital fasciculus

Figure E. 7
Figure E.7 TractoInferno subject 1099: Right arcuate fasciculus.Intensity thresholds are as described in Table ??